Integrative review of intelligent nuchal translucency for genetic disorder

Nuchal Translucency (NT) screening is a critical prenatal diagnostic tool used to detect chromosomal abnormalities and congenital heart defects, yet it has limitations in accuracy and reliability. Despite its importance, research in this area, particularly involving Deep Learning (DL) techniques, remains limited. This survey addresses this gap by collecting and analyzing 53 research papers related to NT screening and detection. The study starts with a systematic paper selection process and followed by a literature review. Additionally, it outlines the general steps involved in conventional NT screening approaches. The analysis and discussion section includes a chronological review of the studies, an examination of the datasets used, and a detailed analysis of the performance of conventional NT approaches, which is further broken down into performance metrics and statistical tests. The findings reveal significant research gaps and challenges in traditional NT screening methods, underscoring the need for more efficient Machine Learning (ML) and DL-based NT detection approaches. This study highlights the importance of advancing DL techniques to improve the detection and diagnosis of chromosomal abnormalities and congenital heart defects through NT screening.